Nearly all Internet users interact with search engines on a daily basis for locating the information they desire. Search engines provide a convenient access point to a wealth of information related to nearly every subject imaginable and research has enabled a search engine to locate increasingly relevant results based upon a user query.
Despite the popularity of web search engines, little currently distinguishes user interaction with one engine from another. For example, the search results currently provided by Yahoo! and others are similar in their presentation, thus failing to provide any impetus for switching to or staying with any given search engine. Also, search engines are often described as a “passthrough” experience; that is, a user merely views the search engine as a temporary stop on the path to their desired page. This mentality makes it more difficult to efficiently monetize the services of the search engine, since the user has an incentive to leave the page as quickly as possible.
Additionally, current search engine techniques do not adequately leverage the wide variety of vertical searches and properties currently available. Current user interfaces require users to explicitly indicate that they want results from each vertical individually and many users are unaware that vertical searches exist, or how a given user may be able to utilize such vertical searches.
Currently search engines use a wide variety of sophisticated algorithms to select relevant search results from an index of content items but ignore the valuable information for presentation of search results that the search engine may gather by monitoring how users interact with the search results. This results in a static presentation of data, as opposed to a dynamic display that adjusts to user tendencies and preferences.